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Research Articles

Molecular docking and molecular dynamics simulation approach to screen natural compounds for inhibition of Xanthomonas oryzae pv. Oryzae by targeting peptide deformylase

, , , ORCID Icon &
Pages 823-840
Received 11 Oct 2019
Accepted 13 Jan 2020
Accepted author version posted online: 22 Jan 2020
Published online: 30 Jan 2020

Abstract

Xanthomonas oryzae pv. Oryzae (Xoo) causes bacterial leaf blight (BLB) of rice which results in a huge loss in production. Many chemicals are used to control BLB disease. However, these chemicals are toxic to the environments, animals and human beings. Thus, there is a demand to discover potential and safe natural pesticides to manage BLB disease successfully. Therefore, we screened a library of phytochemicals of different plants having antibacterial activity by targeting Peptide Deformylase (PDF) of Xoo using in silico techniques. A library of 318 phytochemicals was prepared and subjected to rigid and flexible molecular docking against PDF followed by molecular dynamics simulation and free energy analysis of protein-ligand complexes. The results of virtual screening showed that 14 compounds from different plants have good binding energy as compare to reference molecule (3 R)-2,3-dihydro[1,3] thiazolo [3,2 a]benzimidazol-3-ol) (-7.7 kcal mol−1). Out of 14 hit compounds, eight compounds that were selected based on binding energy were analyzed by Molecular dynamic (MD) simulation. Analysis of MD simulation revealed that eight compounds namely; Bisdemethoxycurcumin, Rosmarinic acid, Piperanine, Dihydropiperlonguminine, Piperdardine, Dihydrocurcumin and Lonhumosides B achieved good stability during the 80 ns MD simulation at 300 K in term of the RMSD. Further, we calculated RMSF, RG, SASA, and interaction energy after 40 ns due to showing the stability of complexes. From our results, we conclude that these natural compounds could inhibit Xoo by targeting PDF receptor and can be used as potential bactericidal candidates against BLB disease of rice against Xoo and other bacteria.

Communicated by Ramaswamy H. Sarma

Acknowledgements

The authors acknowledge the Department of Botany, Kumaun University, SSJ Campus, Almora for providing basic facilities to conduct this research work. Authors also acknowledge to Kumaun University, Nainital for providing high-speed internet facility. We also extend our acknowledge to Rashtriya Uchchattar Shiksha Abhiyan (RUSA), Ministry of Human Resource Development, Government of India to provide Computational infrastructure for the establishment of Bioinformatics Centre in Kumaun University, SSJ Campus, Almora.

Author contributions

Tushar Joshi planned the outline of this research and conducted docking and simulation and has written this manuscript. Tanuja Joshi helps to analyze MD and post-MD simulation. Priyanka Sharma contributed to the construction and analysis of Lig plots. Dr. Subhash Chandra is a supervisor of Tushar Joshi. He has guided in the methodology troubleshooting of computational techniques. Dr. Veena Pande is a co-supervisor and she has provided her critical analysis in this manuscript.

Additional information

Funding

There was no funding source to carry out this research work.

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